nlp engineer

Tekskills Inc.

<div>
 
 
 Job Title: NLP Engineer
 
 
 
 
 Location: Hartford, CT 06156 (Onsite)
 
 
 
 
 Duration: 12 Months
 
 
 
 
 
 
 Must Have Skills
 
 
 <ul>
 <li>
 IBM watson X Orchestrate
 </li>
 <li>
 NLP
 </li>
 <li>
 Java, Node.js, or Python
 </li>
 </ul>
 
 
 
 
 Detailed Job Description
 
 
 <ul>
 <li>
 5 years software delivery experience3 years of Chatbot development experience with IBM WatsonX Orchestrate, or any other similar chatbot conversational AI tool i.e Google Dialogflow CX, LivePerson, Amazon Lex, Kore.ai3 years training and improving intent recognition by curating the appropriate training data sets3 years applying Conversational AI best practices e.g. NLP and training data best practices1 years of experience in CICD, Git, unittesting and source code management1 years of knowledge
 </li>
 </ul>
 
 
</div>

Chatbot Developer

akwad

<div>Job Overview: 
We are seeking a talented and experienced AI/ML Engineer to design, develop, and deploy cutting-edge artificial intelligence and machine learning solutions. This role focuses on the core ML lifecycle, from data handling and model development to deployment, optimization, and monitoring in production environments. The ideal candidate will be passionate about leveraging the latest advancements in AI, particularly in areas like Large Language Models (LLMs) and Natural Language Processing (NLP), to build intelligent systems that drive innovation and solve complex problems. 
Key Responsibilities:
<ul><li>
Design, build, train, and fine-tune various machine learning models, with a strong focus on Large Language Models (LLMs) and Natural Language Processing (NLP) models.
</li><li>Collaborate with data scientists and engineers to acquire, preprocess, and manage data required for model training and evaluation.
</li><li>Implement and utilize AI/ML frameworks and libraries (e.g., PyTorch, TensorFlow, scikit-learn, Hugging Face transformers).
</li><li>Develop and implement APIs and integration points to make AI/ML models and services accessible to other engineering teams and systems.
</li><li>Deploy, manage, and monitor models and AI services in production environments, ensuring performance, scalability, and reliability.
</li><li>Utilize specialized AI development tools and frameworks such as LangChain, AutoGen, or other intelligent agent frameworks.
</li><li>Implement MLOps practices for model versioning, continuous integration/continuous deployment (CI/CD), monitoring, and retraining.
</li><li>Optimize models and inference pipelines for performance, efficiency, and cost-effectiveness.
</li><li>Stay updated with the latest research, techniques, and tools in the AI/ML field and propose new approaches.
</li><li>Collaborate effectively with product managers, data scientists, and other engineering teams (e.g., backend, frontend) to translate requirements into technical designs and integrate AI capabilities into products.
</li></ul>
Required Skills and Experience:
<ul><li>
4+ years of experience in a technical role with a strong focus on Machine Learning and AI development (ideally 2+ years dedicated AI/ML experience).
</li><li>Proficiency in Python and standard ML/AI libraries (e.g., NumPy, Pandas, scikit-learn, TensorFlow, PyTorch).
</li><li>Solid understanding of core Machine Learning concepts, algorithms, model evaluation techniques, and deployment strategies.
</li><li>Hands-on experience building, training, and deploying models, especially LLMs and NLP models.
</li><li>Experience working with LLM APIs (e.g., OpenAI, Anthropic) and relevant libraries/frameworks (e.g., Hugging Face transformers, LangChain, AutoGen).
</li><li>Familiarity with vector databases/stores (e.g., Pinecone, Weaviate, FAISS) and techniques like RAG (Retrieval Augmented Generation).
</li><li>Experience with model deployment tools and MLOps practices.
</li><li>Familiarity with cloud platforms (AWS, GCP, Azure) and containerization technologies (Docker, Kubernetes) for model deployment.
</li><li>Understanding of API design principles for serving machine learning models.
</li><li>Strong problem-solving skills and ability to translate business problems into technical AI/ML solutions.
</li><li>Excellent communication and collaboration skills.
</li></ul>
Nice-to-Haves:
<ul><li>
Experience with specific cloud ML services (e.g., AWS SageMaker, Google AI Platform/Vertex AI, Azure ML).
</li><li>Knowledge of data engineering pipelines and ETL processes.
</li><li>Experience with distributed training frameworks.
</li><li>Contributions to open-source AI/ML projects.
</li><li>Advanced degree (Master's or PhD) in Computer Science, Machine Learning, Data Science, or a related quantitative field.</li></ul></div>

AI/ML Engineer

Openkyber

<div>Job Title: AI / ML Engineer 
Location: Dallas, TX or Memphis, TN Hybrid 
Duration: 6+ Months
Project Role : AI / ML Engineer
Project Role Description : Develops applications and systems that utilize AI tools, Cloud AI services, with proper cloud or on-prem application pipeline with production ready quality. Be able to apply GenAI models as part of the solution and developing AI applications using LLMs, RAG (Retrieval-Augmented Generation), and particularly agentic AI solution. Could also include but not limited to deep learning, neural networks, chatbots, image processing.
Must have skills :
<ul><li>Advanced knowledge of Python specifically for machine learning and data science.</li>
<li>Experience with LLM frameworks such as LangChain, LlamaIndex, Semantic Kernel, or AutoGen.</li>
<li>Proficiency in cloud services related to ML/AI (e.g., Azure, OpenAI, Hugging Face, AWS, Google Cloud Platform).</li>
<li>Extensive experience in AI/ML development, particularly in NLP, and machine learning domains.</li>
<li>Hands-on experience in developing AI applications using LLMs, RAG (Retrieval-Augmented Generation), and particularly agentic AI solutions is essential</li>
<li>Proficiency in designing and maintaining AI/ML solutions that are cost-effective, accurate, and scalable.</li>
<li>Exceptional problem-solving skills and the ability to think analytically.</li>
<li>Strong communication and interpersonal skills, with the aptitude to navigate complex project requirements with clients and stakeholders.</li>
</ul>Nice to have: Certification as an Azure AI Engineer Associate or equivalent credentials is highly advantageous.
Experience with ML/DL frameworks like TensorFlow, Keras, PyTorch, and scikit-learn.
Experience with C# or Java, node.js.
With Regards, OpenKyber 
7525 Mitchell Road, Suite 106, Eden Prairie, MN 55344 
Email ID - hirings@openkyber.com
For applications and inquiries, contact: hirings@openkyber.com</div>

OCI AI Services Engineer

Apple

Imagine what you could do here. At Apple, new ideas have a way of becoming great products, services, and customer experiences very quickly. Bring passion and dedication to your job and there's no telling what you could accomplish. 
 
Are you passionate about taking AI from prototype to production at scale? 
 
Do you enjoy the craft of prompt engineering, retrieval optimization, and grounding? 
 
Can you build AI systems that are not just impressive demos, but reliable production tools? 
 
The Applied Data Science team within Legal Operations is building production-grade AI for a global legal organization. The AI/ML Engineer role is central to this mission - prototyping AI solutions, then scaling them to production systems that attorneys rely on every day. 
 
Description 
 
The AI/ML Engineer builds AI capabilities from prototype to production. You will develop prompt engineering solutions, RAG pipelines, AI agents, and evaluation frameworks - starting with rapid prototypes to validate use cases, then engineering them into scalable, production-grade systems. This role requires both the creativity to explore what's possible and the rigor to build what's reliable.&quot;,&quot;responsibilities&quot;:&quot;Prototype AI solutions to rapidly validate use cases and demonstrate feasibility 
 
Scale successful prototypes into production-grade systems with reliability, monitoring, and maintainability 
 
Implement prompt engineering solutions optimized for legal use cases 
 
Build and optimize RAG (Retrieval-Augmented Generation) pipelines using vector databases and knowledge graphs 
 
Develop context engineering approaches that leverage the semantic layer for improved accuracy 
 
Implement grounding mechanisms to reduce hallucinations and improve factual accuracy 
 
Build evaluation frameworks to measure AI accuracy, relevance, and safety across use cases 
 
Integrate AI capabilities with legal workflows (CLM, matter management, eBilling) 
 
Develop AI agent solutions for automation use cases across legal operations 
 
Implement guardrails and safety mechanisms for production AI systems 
 
Collaborate with AI Architect on system design and technical standards 
 
Support AI Product Developers with APIs, integration patterns, and technical guidance 
 
Preferred Qualifications 
 
Experience with LangChain, LlamaIndex, or similar LLM orchestration frameworks 
 
Experience with agentic AI frameworks (LangGraph, CrewAI, or similar) 
 
Familiarity with knowledge graphs and GraphRAG patterns 
 
Experience with AI evaluation tools (RAGAS, DeepEval, or similar) 
 
Knowledge of legal domain and legal NLP applications 
 
Experience with guardrails and safety frameworks (Guardrails AI, NeMo Guardrails) 
 
Understanding of MCP (Model Context Protocol) or similar integration patterns 
 
Experience deploying and monitoring AI systems at scale 
 
Track record of shipping AI products that users rely on 
 
Minimum Qualifications 
 
4+ years of delivering solutions in AI/ML engineering, NLP, or related roles 
 
Strong proficiency in Python and ML frameworks (PyTorch, TensorFlow, or similar) 
 
Experience with LLM APIs (OpenAI, Anthropic, or similar) 
 
Experience with RAG architectures and vector databases 
 
Understanding of prompt engineering techniques and best practices 
 
Experience taking AI systems from prototype to production 
 
Experience with evaluation frameworks for AI systems 
 
Supporting AI applications in production 
 
Apple is an equal opportunity employer that is committed to inclusion and diversity. We seek to promote equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics. Learn more about your EEO rights as an applicant . 
 
Pay &amp; Benefits 
 
At Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $172,100 and $258,600, and your base pay will depend on your skills, qualifications, experience, and location. 
 
Apple employees also have the opportunity to become an Apple shareholder through participation in Apple's discretionary employee stock programs. Apple employees are eligible for discretionary restricted stock unit awards, and can purchase Apple stock at a discount if voluntarily participating in Apple's Employee Stock Purchase Plan. You'll also receive benefits including: Comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and for formal education related to advancing your career at Apple, reimbursement for certain educational expenses - including tuition. Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation. Learn more about Apple Benefits. 
 
Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.

AI/ML Engineer, Applied Data Science

Encora Inc.

<div>
 We are seeking an
 
 AI/ML Engineer &ndash; Agents
 
 to help build the core intelligence layer of our AI-powered MarTech and AdTech platform. This role will focus on designing, developing, and deploying
 
 agentic AI systems
 
 ,
 
 LLM-powered applications
 
 , and
 
 real-time inference pipelines
 
 that drive intelligent automation, personalization, and decision-making at scale.
 
 
 This is a high-impact, hands-on engineering role for someone who thrives in fast-moving environments and wants to help shape next-generation AI products from the ground up.
 
 
 
 Key Responsibilities
 
 
 
 <ul>
 <li>
 Design and deploy agentic AI systems using frameworks such as LangGraph, AutoGen, CrewAI, or similar.
 </li>
 <li>
 Build and scale LLM/GenAI applications for MarTech and AdTech use cases, including content generation, campaign optimization, audience segmentation, personalization, and workflow automation.
 </li>
 <li>
 Fine-tune and optimize LLMs/SLMs for domain-specific tasks such as classification, extraction, recommendation, and intent understanding.
 </li>
 <li>
 Develop and manage training and inference pipelines for production-scale ML systems.
 </li>
 <li>
 Build scalable infrastructure for real-time and batch inference, experimentation, and deployment.
 </li>
 <li>
 Implement best practices for evaluation, A/B testing, model monitoring, and continuous improvement.
 </li>
 <li>
 Partner closely with product, data, and engineering teams to turn prototypes and research into production-ready AI services.
 </li>
 <li>
 Rapidly prototype and apply emerging research to practical product use cases.
 
 
 </li>
 </ul>
 
 Qualifications
 
 
 
 <ul>
 <li>
 
 3+ years
 
 of experience in AI/ML engineering, machine learning, or applied NLP roles.
 </li>
 <li>
 Master&rsquo;s degree in Computer Science, Engineering, or a related field required; PhD preferred.
 </li>
 <li>
 Hands-on experience with agent-based AI frameworks such as LangGraph, AutoGen, CrewAI, or similar.
 </li>
 <li>
 Strong expertise in deep learning and natural language processing using frameworks such as PyTorch or TensorFlow.
 </li>
 <li>
 Experience fine-tuning and deploying foundation models such as LLaMA, Mistral, or similar.
 </li>
 <li>
 Strong experience with Hugging Face, LoRA, PEFT, and modern fine-tuning workflows.
 </li>
 <li>
 Experience with RAG pipelines, vector databases, semantic search, and embedding optimization tools such as FAISS, Pinecone, or PGVector.
 </li>
 <li>
 Experience deploying ML systems in cloud environments such as AWS, GCP, or Azure.
 </li>
 <li>
 Strong software engineering skills in Python, APIs, microservices, and containerized environments such as Docker and Kubernetes.
 </li>
 <li>
 Solid understanding of GPU optimization, distributed training, and inference performance tuning.
 
 
 </li>
 </ul>
 
 Preferred Qualifications
 
 
 
 <ul>
 <li>
 Experience in MarTech, AdTech, personalization, targeting, or attribution systems.
 </li>
 <li>
 Experience with real-time decisioning or ad-serving systems.
 </li>
 <li>
 Contributions to open-source AI/LLM frameworks or published research.
 </li>
 <li>
 Prior experience in a startup or high-growth environment.
 </li>
 </ul>
</div>

Genpact

<div><div><div>Ready to build the future with AI? 
At Genpact, we don&rsquo;t just keep up with technology&mdash;we set the pace. AI and digital innovation are redefining industries, and we&rsquo;re leading the charge. Genpact&rsquo;s AI Gigafactory, our industry-first accelerator, is an example of how we&rsquo;re scaling advanced technology solutions to help global enterprises work smarter, grow faster, and transform at scale. From large-scale models to agentic AI, our breakthrough solutions tackle companies&rsquo; most complex challenges.</div><div>
If you thrive in a fast-moving, innovation-driven environment, love building and deploying cutting-edge AI solutions, and want to push the boundaries of what&rsquo;s possible, this is your moment.</div><div>
Genpact (NYSE: G) is an advanced technology services and solutions company that delivers lasting value for leading enterprises globally. Through our deep business knowledge, operational excellence, and cutting-edge solutions &ndash; we help companies across industries get ahead and stay ahead. Powered by curiosity, courage, and innovation, our teams implement data, technology, and AI to create tomorrow, today. Get to know us at genpact.com and on LinkedIn, X, YouTube, and Facebook. 
 
Inviting applications for the role of Consultant - Artificial Intelligence Developer 
In this role, you will be responsible for creating cutting-edge artificial intelligence solutions that possess a broad understanding of diverse tasks and domains. You will contribute to the development of intelligent systems capable of adapting and learning across a wide range of applications. 
 
Responsibilities 
<ul><li>Build agents/components that reason, plan and act.</li><li>Implement frameworks, develop memory and tool-use capabilities, collaborate with prompt engineers</li><li>Design and implement algorithms that enable the General AI system to acquire new knowledge efficiently and adapt to evolving tasks seamlessly.</li><li>Develop mechanisms for the General AI to perform various tasks, such as natural language understanding, image recognition, and decision-making, ensuring a holistic and versatile skill set.</li><li>Implement continual learning strategies that allow the General AI to adapt and improve its performance over time, learning from both labelled and unlabelled data.</li><li>Collaborate with specialists from different domains to integrate domain-specific knowledge and ensure the General AI's applicability in diverse real-world scenarios.</li><li>Incorporate ethical considerations into the design and development of the General AI, addressing issues related to bias, fairness, and transparency in AI decision-making processes.</li><li>Optimize the General AI system for scalability, ensuring efficient performance across different hardware and deployment environments.</li><li>Engage in interdisciplinary research, staying updated on advancements in AI, cognitive science, and related fields, and applying relevant findings to enhance the capabilities of General AI.</li><li>Understanding business objectives and developing models that help to achieve them, along with metrics to track their progress.</li><li>Verifying data quality, and/or ensuring it via data cleaning</li><li>Defining validation strategies &amp; data augmentation pipelines</li><li>Designing, developing, and researching Machine Learning systems, models, and schemes</li><li>Good working knowledge on deep learning and advanced NLP techniques</li><li>Analyzing the use cases of ML algorithms and ranking them by their success probability</li><li>Should be excellent with Rasa Framework or any other chatbot interface.</li><li>Performing statistical analysis and using results to improve models.</li><li>Training and retraining ML systems and models in real-world situations</li><li>Visualizing data for deeper insights</li><li>Hands-On with Service / Incident Management tools: JIRA / ServiceNow</li><li>Knowledge and experience with Software Version Control systems: GIT, SVN etc.</li></ul></div><div>
Qualification 
(Minimum Qualification) 
<ul><li>BE/B Tech/MCA</li><li>Excellent written and verbal communication skills</li><li>Basic understanding of Investment Management/financial services domain knowledge</li></ul></div><div>
Preferred Qualifications/Skill 
<ul><li>Create comprehensive documentation of algorithms, models, and methodologies, and actively contribute to knowledge transfer within the team to foster a collaborative and learning-oriented environment.</li><li>Demonstrated expertise in artificial intelligence, machine learning, and deep learning.</li><li>Strong programming skills, preferably in Python, and experience with popular AI frameworks (e.g., TensorFlow, PyTorch)</li><li>Experience with reinforcement learning and transfer learning in the context of General AI.</li><li>Knowledge of cognitive science principles and their application to AI development Skill Set</li><li>Machine learning</li><li>NLP and Advanced NLP</li><li>Public</li><li>Deep Learning (CNN,ANN,RNN)</li><li>Rasa</li><li>Pandas, sql</li><li>Python</li><li>Django, Flask</li><li>Tensorflow</li><li>Keras</li><li>Chatbot Development</li><li>Agile</li><li>AWS</li><li>GIT</li></ul></div><div>
Why join Genpact? 
<ul><li>Lead AI-first transformation &ndash; Build and scale AI solutions that redefine industries</li><li>Make an impact &ndash; Drive change for global enterprises and solve business challenges that matter</li><li>Accelerate your career&mdash;Gain hands-on experience, world-class training, mentorship, and AI certifications to advance your skills</li><li>Grow with the best &ndash; Learn from top engineers, data scientists, and AI experts in a dynamic, fast-moving workplace</li><li>Committed to ethical AI &ndash; Work in an environment where governance, transparency, and security are at the core of everything we build</li><li>Thrive in a values-driven culture &ndash; Our courage, curiosity, and incisiveness - built on a foundation of integrity and inclusion - allow your ideas to fuel progress</li></ul>
Come join the 140,000+ coders, tech shapers, and growth makers at Genpact and take your career in the only direction that matters: Up. 
Let&rsquo;s build tomorrow together. 
The approximate annual base compensation range for this position is $60000 to $75000. The actual offer, reflecting the total compensation package plus benefits, will be determined by a number of factors which include but are not limited to the applicant&rsquo;s experience, knowledge, skills, and abilities; geographic location; and internal equity 
<ul><li>Work-from-Anywhere Roles &ndash; &ldquo;Los Angeles California-based candidates are not eligible for this role&rdquo;</li><li>Location-based Roles (e.g., Richardson roles &ndash; metro area can be adjusted by role location) &ndash; &ldquo;Los Angeles, California based candidates are not eligible for this role. &lt;Dallas Metro&gt; area candidates are eligible for this role only.&rdquo;</li></ul></div><div> 
Genpact is an Equal Opportunity Employer and considers applicants for all positions without regard to race, color, religion or belief, sex, age, national origin, citizenship status, marital status, military/veteran status, genetic information, sexual orientation, gender identity, physical or mental disability or any other characteristic protected by applicable laws. Genpact is committed to creating a dynamic work environment that values respect and integrity, customer focus, and innovation. 
Furthermore, please do note that Genpact does not charge fees to process job applications and applicants are not required to pay to participate in our hiring process in any other way. Examples of such scams include purchasing a 'starter kit,' paying to apply, or purchasing equipment or training.</div></div> 
JobConsultant
Primary LocationUSA-New York
ScheduleFull-time
Education LevelBachelor's / Graduation / Equivalent
Job PostingApr 13, 2026, 9:02:35 AM
Unposting DateOngoing
Master Skills ListConsulting
Job CategoryFull Time</div>

Consultant - Artificial Intelligence Developer

Adobe

About the Role
 Join our Digital Employee Experience team as a Context Engineer and help define an emerging discipline at the intersection of language, system design, and enterprise operations. You'll work alongside diverse functional roles, applying hands-on expertise with large language models (LLMs) to
 improve the human experience at work. You'll own the design and implementation of pipelines that assemble the right mix of inputs—instructions, frameworks, standards, tools, and memory—ensuring models respond accurately and safely at scale, with direct impact on employee productivity and
 experience.
 What You'll Do
 <ul>
<li>Partner cross-functionally to identify and structure the enterprise knowledge LLMs need to enhance productivity across business functions.</li>
<li>Build and maintain context templates combining few-shot examples, chain-of-thought scaffolding, and structured formatting.</li>
<li>Design, implement, and iterate on context pipelines that assemble and deliver information to LLMs reliably in production.</li>
<li>Develop memory mechanisms to manage conversational state across sessions, including summarization, pruning, and context compression strategies.</li>
<li>Own optimization of cost, latency, and reliability—balancing token limits, response time, and accuracy for production workloads.</li>
<li>Establish and document best practices for context engineering, contributing to standards adopted across the enterprise.</li>
<li>Contribute to code reviews, technical discussions, and the growth of the broader team.</li>
</ul>
What You Need to Succeed
 <ul>
<li>Bachelor's or Master's degree in Computer Science, Data Science, Artificial Intelligence, or a related field.</li>
<li>2–4 years of professional experience building systems or applications that leverage LLMs or NLP in a production environment.</li>
<li>Proficiency in Python and hands-on experience with frameworks such as LangChain, Hugging Face, PyTorch, or TensorFlow.</li>
<li>Solid understanding of tokenization, prompt formatting, context window constraints, and retrieval-augmented generation (RAG) patterns.</li>
<li>Experience working with APIs, data structures, and JSON in real-world integrations.</li>
<li>Strong problem-solving skills with a track record of diagnosing and resolving ambiguous technical challenges independently.</li>
<li>Clear communicator—able to align stakeholders and translate complex concepts for non-technical audiences.</li>
<li>Collaborative by default, with a drive to share knowledge and raise the quality of work around you.</li>
</ul>
About Adobe
 Adobe empowers everyone to create through innovative platforms and tools that unleash creativity, productivity and personalized customer experiences. Adobe’s industry-leading offerings including Adobe Acrobat Studio, Adobe Express, Adobe Firefly, Creative Cloud, Adobe Experience Platform, Adobe Experience Manager, and GenStudio enable people and businesses to turn ideas into impact, powered by AI and driven by human ingenuity.
 
Our 30,000+ employees worldwide are creating the future and raising the bar as we drive the next decade of growth. We’re on a mission to hire the very best and believe in creating a company culture where all employees are empowered to make an impact. At Adobe, we believe that great ideas can come from anywhere in the organization. The next big idea could be yours.
 
Let’s Adobe together
 At Adobe, we believe in creating a company culture where all employees are empowered to make an impact. Learn more about Adobe life, including our values and culture , focus on people, purpose and community , Adobe for All , comprehensive benefits programs , the stories we tell , the customers we serve, and how you can help us advance our mission of empowering everyone to create.
 
Adobe is proud to be an Equal Employment Opportunity employer. We do not discriminate based on gender, race or color, ethnicity or national origin, age, disability, religion, sexual orientation, gender identity or expression, veteran status, or any other protected characteristic. Learn more.
 
Adobe aims to make our Careers website and recruiting process accessible to any and all users. If you have a disability or special need that requires accommodation to navigate our website or complete the application process, email accommodations@adobe.com or call +1 408-536-3015.
 
AI Use Guidelines for Interviews: 
Our interviews are designed to reflect your own skills and thinking. The use of AI or recording tools during live interviews is not permitted unless explicitly invited by the interviewer or approved in advance as part of a reasonable accommodation. If these tools are used inappropriately or in a way that misrepresents your work, your application may not move forward in the process.
 
At Adobe, we empower employees to innovate with AI — and we look for candidates eager to do the same. As part of the hiring experience, we provide clear guidance on where AI is encouraged during the process and where it’s restricted during live interviews. See how we think about AI in the hiring experience .
 
Expected Pay Range: Our compensation reflects the cost of labor across several U.S. geographic markets, and we pay differently based on those defined markets. The U.S. pay range for this position is $114,100 -- $214,950 annually. Pay within this range varies by work location and may also depend on job-related knowledge, skills, and experience. Your recruiter can share more about the specific salary range for the job location during the hiring process.
 
At Adobe, for sales roles starting salaries are expressed as total target compensation (TTC = base + commission), and short-term incentives are in the form of sales commission plans. Non-sales roles starting salaries are expressed as base salary and short-term incentives are in the form of the Annual Incentive Plan (AIP).
 
In addition, certain roles may be eligible for long-term incentives in the form of a new hire equity award.
 
State-Specific Notices: 
California : 
Fair Chance Ordinances
 Adobe will consider qualified applicants with arrest or conviction records for employment in accordance with state and local laws and “fair chance” ordinances.
 
Colorado: 
Application Window Notice
 
If this role is open to hiring in Colorado (as listed on the job posting), the application window will remain open until at least the date and time stated above in Pacific Time, in compliance with Colorado pay transparency regulations. If this role does not have Colorado listed as a hiring location, no specific application window applies, and the posting may close at any time based on hiring needs.
 
Massachusetts: 
Massachusetts Legal Notice
 It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability.

AI Context Engineer

Search 689+ Nlp engineer jobs near you this June. New roles added regularly across leading industries. Apply today.

689 nlp engineer jobs Near Me

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